Interference Management with Reflective In-Band Full-Duplex NOMA for Secure 6G Wireless Communication Systems
The electromagnetic spectrum is used as a medium for modern wireless communication. Most of the spectrum is being utilized by the existing communication system. For technological breakthroughs and fulfilling the demands of better utilization of such natural resources, a novel Reflective In-Band Full...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/7/2508 |
| _version_ | 1797437814246211584 |
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| author | Rabia Khan Nyasha Tsiga Rameez Asif |
| author_facet | Rabia Khan Nyasha Tsiga Rameez Asif |
| author_sort | Rabia Khan |
| collection | DOAJ |
| description | The electromagnetic spectrum is used as a medium for modern wireless communication. Most of the spectrum is being utilized by the existing communication system. For technological breakthroughs and fulfilling the demands of better utilization of such natural resources, a novel Reflective In-Band Full-Duplex (R-IBFD) cooperative communication scheme is proposed in this article that involves Full-Duplex (FD) and Non-Orthogonal Multiple Access (NOMA) technologies. The proposed R-IBFD provides efficient use of spectrum with better system parameters including Secrecy Outage Probability (SOP), throughput, data rate and secrecy capacity to fulfil the requirements of a smart city for 6th Generation (6thG or 6G). The proposed system targets the requirement of new algorithms that contribute towards better change and bring the technological revolution in the requirements of 6G. In this article, the proposed R-IBFD mainly contributes towards co-channel interference and security problem. The In-Band Full-Duplex mode devices face higher co-channel interference in between their own transmission and receiving antenna. R-IBFD minimizes the effect of such interference and assists in the security of a required wireless communication system. For a better understanding of the system contribution, the improvement of secrecy capacity and interference with R-IBFD is discussed with the help of SOP derivation, equations and simulation results. A machine learning genetic algorithm is one of the optimization tools which is being used to maximize the secrecy capacity. |
| first_indexed | 2024-03-09T11:28:04Z |
| format | Article |
| id | doaj.art-f04b5de9c8d04c58941fdedac63838d3 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T11:28:04Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-f04b5de9c8d04c58941fdedac63838d32023-11-30T23:59:52ZengMDPI AGSensors1424-82202022-03-01227250810.3390/s22072508Interference Management with Reflective In-Band Full-Duplex NOMA for Secure 6G Wireless Communication SystemsRabia Khan0Nyasha Tsiga1Rameez Asif2Power Networks Demonstration Centre, University of Strathclyde, Glasgow G1 1XH, UKMechanical Engineering, Moscow Automobile and Road Construction State Technical University (MADI), 125319 Moscow, RussiaSchool of Computing Sciences, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UKThe electromagnetic spectrum is used as a medium for modern wireless communication. Most of the spectrum is being utilized by the existing communication system. For technological breakthroughs and fulfilling the demands of better utilization of such natural resources, a novel Reflective In-Band Full-Duplex (R-IBFD) cooperative communication scheme is proposed in this article that involves Full-Duplex (FD) and Non-Orthogonal Multiple Access (NOMA) technologies. The proposed R-IBFD provides efficient use of spectrum with better system parameters including Secrecy Outage Probability (SOP), throughput, data rate and secrecy capacity to fulfil the requirements of a smart city for 6th Generation (6thG or 6G). The proposed system targets the requirement of new algorithms that contribute towards better change and bring the technological revolution in the requirements of 6G. In this article, the proposed R-IBFD mainly contributes towards co-channel interference and security problem. The In-Band Full-Duplex mode devices face higher co-channel interference in between their own transmission and receiving antenna. R-IBFD minimizes the effect of such interference and assists in the security of a required wireless communication system. For a better understanding of the system contribution, the improvement of secrecy capacity and interference with R-IBFD is discussed with the help of SOP derivation, equations and simulation results. A machine learning genetic algorithm is one of the optimization tools which is being used to maximize the secrecy capacity.https://www.mdpi.com/1424-8220/22/7/25086GB5Gin-band full-duplexreflective-in-band full-duplexnon-orthogonal multiple accessmachine learning genetic algorithm |
| spellingShingle | Rabia Khan Nyasha Tsiga Rameez Asif Interference Management with Reflective In-Band Full-Duplex NOMA for Secure 6G Wireless Communication Systems Sensors 6G B5G in-band full-duplex reflective-in-band full-duplex non-orthogonal multiple access machine learning genetic algorithm |
| title | Interference Management with Reflective In-Band Full-Duplex NOMA for Secure 6G Wireless Communication Systems |
| title_full | Interference Management with Reflective In-Band Full-Duplex NOMA for Secure 6G Wireless Communication Systems |
| title_fullStr | Interference Management with Reflective In-Band Full-Duplex NOMA for Secure 6G Wireless Communication Systems |
| title_full_unstemmed | Interference Management with Reflective In-Band Full-Duplex NOMA for Secure 6G Wireless Communication Systems |
| title_short | Interference Management with Reflective In-Band Full-Duplex NOMA for Secure 6G Wireless Communication Systems |
| title_sort | interference management with reflective in band full duplex noma for secure 6g wireless communication systems |
| topic | 6G B5G in-band full-duplex reflective-in-band full-duplex non-orthogonal multiple access machine learning genetic algorithm |
| url | https://www.mdpi.com/1424-8220/22/7/2508 |
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